Performing chemical textual analysis

ABSTRACT

A computer-implemented method according to one embodiment includes identifying a textual document, determining chemical data within the textual document, performing an analysis of the chemical data to identify a chemical pathway, and calculating a probability score for the chemical pathway.

BACKGROUND

The present invention relates to textual analysis, and morespecifically, this invention relates to performing textual analysis froma chemical perspective.

The analysis of chemical components and reactions is a major componentof chemical development. However, physical chemical experimentation in awet lab is time and resource intensive, as well as potentiallyhazardous. There is therefore a need to minimize undue experimentation.

SUMMARY

A computer-implemented method according to one embodiment includesidentifying a textual document, determining chemical data within thetextual document, performing an analysis of the chemical data toidentify a chemical pathway, and calculating a probability score for thechemical pathway.

Other aspects and embodiments of the present invention will becomeapparent from the following detailed description, which, when taken inconjunction with the drawings, illustrate by way of example theprinciples of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a network architecture, in accordance with oneembodiment.

FIG. 2 shows a representative hardware environment that may beassociated with the servers and/or clients of FIG. 1, in accordance withone embodiment.

FIG. 3 illustrates a tiered data storage system in accordance with oneembodiment.

FIG. 4 illustrates a method for performing chemical textual analysis, inaccordance with one embodiment.

FIG. 5 illustrates an exemplary chemical pathway discovery environment,in accordance with one embodiment.

FIG. 6 illustrates a method for performing reaction corpus scoring, inaccordance with one embodiment.

DETAILED DESCRIPTION

The following description discloses several preferred embodiments ofsystems, methods and computer program products for performing chemicaltextual analysis. Various embodiments provide a method to identify andanalyze chemical terminology within textual data.

The following description is made for the purpose of illustrating thegeneral principles of the present invention and is not meant to limitthe inventive concepts claimed herein. Further, particular featuresdescribed herein can be used in combination with other describedfeatures in each of the various possible combinations and permutations.

Unless otherwise specifically defined herein, all terms are to be giventheir broadest possible interpretation including meanings implied fromthe specification as well as meanings understood by those skilled in theart and/or as defined in dictionaries, treatises, etc.

It must also be noted that, as used in the specification and theappended claims, the singular forms “a,” “an” and “the” include pluralreferents unless otherwise specified. It will be further understood thatthe terms “includes” and/or “comprising,” when used in thisspecification, specify the presence of stated features, integers, steps,operations, elements, and/or components, but do not preclude thepresence or addition of one or more other features, integers, steps,operations, elements, components, and/or groups thereof.

The following description discloses several preferred embodiments ofsystems, methods and computer program products for performing chemicaltextual analysis.

In one general embodiment, a computer-implemented method includesidentifying a textual document, determining chemical data within thetextual document, performing an analysis of the chemical data toidentify a chemical pathway, and calculating a probability score for thechemical pathway.

In another general embodiment, a computer program product for performingchemical textual analysis comprises a computer readable storage mediumhaving program instructions embodied therewith, wherein the computerreadable storage medium is not a transitory signal per se, and where theprogram instructions are executable by a processor to cause theprocessor to perform a method comprising identifying a textual document,utilizing the processor, determining chemical data within the textualdocument, utilizing the processor, performing an analysis of thechemical data to identify a chemical pathway, utilizing the processor,and calculating a probability score for the chemical pathway, utilizingthe processor.

In another general embodiment, a system includes a processor and logicintegrated with and/or executable by the processor, where he logic isconfigured to identify a textual document, determine chemical datawithin the textual document, perform an analysis of the chemical data toidentify a chemical pathway, and calculate a probability score for thechemical pathway.

FIG. 1 illustrates an architecture 100, in accordance with oneembodiment. As shown in FIG. 1, a plurality of remote networks 102 areprovided including a first remote network 104 and a second remotenetwork 106. A gateway 101 may be coupled between the remote networks102 and a proximate network 108. In the context of the presentarchitecture 100, the networks 104, 106 may each take any formincluding, but not limited to a LAN, a WAN such as the Internet, publicswitched telephone network (PSTN), internal telephone network, etc.

In use, the gateway 101 serves as an entrance point from the remotenetworks 102 to the proximate network 108. As such, the gateway 101 mayfunction as a router, which is capable of directing a given packet ofdata that arrives at the gateway 101, and a switch, which furnishes theactual path in and out of the gateway 101 for a given packet.

Further included is at least one data server 114 coupled to theproximate network 108, and which is accessible from the remote networks102 via the gateway 101. It should be noted that the data server(s) 114may include any type of computing device/groupware. Coupled to each dataserver 114 is a plurality of user devices 116. User devices 116 may alsobe connected directly through one of the networks 104, 106, 108. Suchuser devices 116 may include a desktop computer, lap-top computer,hand-held computer, printer or any other type of logic. It should benoted that a user device 111 may also be directly coupled to any of thenetworks, in one embodiment.

A peripheral 120 or series of peripherals 120, e.g., facsimile machines,printers, networked and/or local storage units or systems, etc., may becoupled to one or more of the networks 104, 106, 108. It should be notedthat databases and/or additional components may be utilized with, orintegrated into, any type of network element coupled to the networks104, 106, 108. In the context of the present description, a networkelement may refer to any component of a network.

According to some approaches, methods and systems described herein maybe implemented with and/or on virtual systems and/or systems whichemulate one or more other systems, such as a UNIX system which emulatesan IBM z/OS environment, a UNIX system which virtually hosts a MICROSOFTWINDOWS environment, a MICROSOFT WINDOWS system which emulates an IBMz/OS environment, etc. This virtualization and/or emulation may beenhanced through the use of VMWARE software, in some embodiments.

In more approaches, one or more networks 104, 106, 108, may represent acluster of systems commonly referred to as a “cloud.” In cloudcomputing, shared resources, such as processing power, peripherals,software, data, servers, etc., are provided to any system in the cloudin an on-demand relationship, thereby allowing access and distributionof services across many computing systems. Cloud computing typicallyinvolves an Internet connection between the systems operating in thecloud, but other techniques of connecting the systems may also be used.

FIG. 2 shows a representative hardware environment associated with auser device 116 and/or server 114 of FIG. 1, in accordance with oneembodiment. Such figure illustrates a typical hardware configuration ofa workstation having a central processing unit 210, such as amicroprocessor, and a number of other units interconnected via a systembus 212.

The workstation shown in FIG. 2 includes a Random Access Memory (RAM)214, Read Only Memory (ROM) 216, an I/O adapter 218 for connectingperipheral devices such as disk storage units 220 to the bus 212, a userinterface adapter 222 for connecting a keyboard 224, a mouse 226, aspeaker 228, a microphone 232, and/or other user interface devices suchas a touch screen and a digital camera (not shown) to the bus 212,communication adapter 234 for connecting the workstation to acommunication network 235 (e.g., a data processing network) and adisplay adapter 236 for connecting the bus 212 to a display device 238.

The workstation may have resident thereon an operating system such asthe Microsoft Windows® Operating System (OS), a MAC OS, a UNIX OS, etc.It will be appreciated that a preferred embodiment may also beimplemented on platforms and operating systems other than thosementioned. A preferred embodiment may be written using XML, C, and/orC++ language, or other programming languages, along with an objectoriented programming methodology. Object oriented programming (OOP),which has become increasingly used to develop complex applications, maybe used.

Now referring to FIG. 3, a storage system 300 is shown according to oneembodiment. Note that some of the elements shown in FIG. 3 may beimplemented as hardware and/or software, according to variousembodiments. The storage system 300 may include a storage system manager312 for communicating with a plurality of media on at least one higherstorage tier 302 and at least one lower storage tier 306. The higherstorage tier(s) 302 preferably may include one or more random accessand/or direct access media 304, such as hard disks in hard disk drives(HDDs), nonvolatile memory (NVM), solid state memory in solid statedrives (SSDs), flash memory, SSD arrays, flash memory arrays, etc.,and/or others noted herein or known in the art. The lower storagetier(s) 306 may preferably include one or more lower performing storagemedia 308, including sequential access media such as magnetic tape intape drives and/or optical media, slower accessing HDDs, sloweraccessing SSDs, etc., and/or others noted herein or known in the art.One or more additional storage tiers 316 may include any combination ofstorage memory media as desired by a designer of the system 300. Also,any of the higher storage tiers 302 and/or the lower storage tiers 306may include some combination of storage devices and/or storage media.

The storage system manager 312 may communicate with the storage media304, 308 on the higher storage tier(s) 302 and lower storage tier(s) 306through a network 310, such as a storage area network (SAN), as shown inFIG. 3, or some other suitable network type. The storage system manager312 may also communicate with one or more host systems (not shown)through a host interface 314, which may or may not be a part of thestorage system manager 312. The storage system manager 312 and/or anyother component of the storage system 300 may be implemented in hardwareand/or software, and may make use of a processor (not shown) forexecuting commands of a type known in the art, such as a centralprocessing unit (CPU), a field programmable gate array (FPGA), anapplication specific integrated circuit (ASIC), etc. Of course, anyarrangement of a storage system may be used, as will be apparent tothose of skill in the art upon reading the present description.

In more embodiments, the storage system 300 may include any number ofdata storage tiers, and may include the same or different storage memorymedia within each storage tier. For example, each data storage tier mayinclude the same type of storage memory media, such as HDDs, SSDs,sequential access media (tape in tape drives, optical disk in opticaldisk drives, etc.), direct access media (CD-ROM, DVD-ROM, etc.), or anycombination of media storage types. In one such configuration, a higherstorage tier 302, may include a majority of SSD storage media forstoring data in a higher performing storage environment, and remainingstorage tiers, including lower storage tier 306 and additional storagetiers 316 may include any combination of SSDs, HDDs, tape drives, etc.,for storing data in a lower performing storage environment. In this way,more frequently accessed data, data having a higher priority, dataneeding to be accessed more quickly, etc., may be stored to the higherstorage tier 302, while data not having one of these attributes may bestored to the additional storage tiers 316, including lower storage tier306. Of course, one of skill in the art, upon reading the presentdescriptions, may devise many other combinations of storage media typesto implement into different storage schemes, according to theembodiments presented herein.

According to some embodiments, the storage system (such as 300) mayinclude logic configured to receive a request to open a data set, logicconfigured to determine if the requested data set is stored to a lowerstorage tier 306 of a tiered data storage system 300 in multipleassociated portions, logic configured to move each associated portion ofthe requested data set to a higher storage tier 302 of the tiered datastorage system 300, and logic configured to assemble the requested dataset on the higher storage tier 302 of the tiered data storage system 300from the associated portions.

Of course, this logic may be implemented as a method on any deviceand/or system or as a computer program product, according to variousembodiments.

Now referring to FIG. 4, a flowchart of a method 400 is shown accordingto one embodiment. The method 400 may be performed in accordance withthe present invention in any of the environments depicted in FIGS. 1-3and 5-6, among others, in various embodiments. Of course, more or lessoperations than those specifically described in FIG. 4 may be includedin method 400, as would be understood by one of skill in the art uponreading the present descriptions.

Each of the steps of the method 400 may be performed by any suitablecomponent of the operating environment. For example, in variousembodiments, the method 400 may be partially or entirely performed byone or more servers, computers, or some other device having one or moreprocessors therein. The processor, e.g., processing circuit(s), chip(s),and/or module(s) implemented in hardware and/or software, and preferablyhaving at least one hardware component may be utilized in any device toperform one or more steps of the method 400. Illustrative processorsinclude, but are not limited to, a central processing unit (CPU), anapplication specific integrated circuit (ASIC), a field programmablegate array (FPGA), etc., combinations thereof, or any other suitablecomputing device known in the art.

As shown in FIG. 4, method 400 may initiate with operation 402, where atextual document is identified. In one embodiment, the textual documentmay include a document written in a natural language usingalphanumerical text. In another embodiment, the textual document may beincluded within a plurality of documents (e.g., a corpus of documents,an index of documents, etc.). In yet another embodiment, the textualdocument may include one or more of a research paper, a publication, atextbook, a blog post, a web page, etc.

In still another embodiment, the textual document may include textassociated with the field of chemistry. For example, the textualdocument may include text that describes one or more chemical components(e.g., one or more chemicals, compounds, molecules, etc.), chemicalreactions, chemical products, chemical byproducts, etc. In anotherembodiment, the textual document may describe one or more experiments,one or more results of the experiments, etc. In yet another embodiment,the textual document may describe one or more known chemical reactions.

Additionally, in one embodiment, the textual document may be retrievedfrom a document database (e.g., a hardware database, a virtual database,a cloud-based database, etc.). In another embodiment, the textualdocument may be created by scanning printed text and converting the textto a digital form using an optical character recognition (OCR)application. In yet another embodiment, the textual document may besubmitted by a user. In still another embodiment, the textual documentmay be identified by a computing device (e.g., a computer, a server, acloud computing device, a mobile computing device, etc.). For example,the textual document may be identified as a result of the computingdevice performing data retrieval (e.g., by crawling one or moredatabases and/or one or more networks, etc.).

Further, as shown in FIG. 4, method 400 may proceed with operation 404,where chemical data is determined within the textual document. In oneembodiment, determining the chemical data may include analyzing thetextual document. For example, analyzing the textual document mayinclude parsing the textual document, identifying components of thetextual document, extracting information from the textual document, etc.

In another embodiment, analyzing the textual document may includeanalyzing one or more relationships between a plurality of terms foundin the textual document. For example, analyzing the textual document mayinclude identifying one or more relationships between words within thetextual document. For instance, the relationships between words withinthe textual document may indicate one or more relationships between oneor more chemical components (e.g., one or more chemicals, compounds,molecules, solvents, etc.).

Further still, in one embodiment, one or more applications may beutilized during the analyzing of the textual document. For example,cheminformatics software (e.g., RDKit, etc.) may be used to translatetextual strings into chemical components such as molecules in astandardized manner. In another example, the cheminformatics softwaremay be used to translate information such as chemical and reactioninformation (e.g., properties, kinetics, etc.) to and from structuraland textual embodiments.

Also, in one embodiment, determining chemical data within the textualdocument may include determining data associated with a plurality ofchemical components (e.g., chemicals, compounds molecules, etc.). Inanother embodiment, the data may include data indicating a structure(e.g., molecular structure, etc.). For example, the determined chemicaldata may include bond order (e.g., single bonds, double bonds, triplebonds, etc.), the aromaticity of a molecule, a ring structure of amolecule, etc. In another embodiment, the chemical data may include adescription of a molecular bond. For example, the chemical data mayinclude an indication as to whether the molecular structure has unboundelectrons that would allow for additional reactivity, etc.

In addition, in one embodiment, the determined chemical data may includean indication of reactiveness (e.g., of a molecule, an element, etc.).For example, the determined chemical data may include the aromaticity ofa molecule, which may suggest a reactiveness of the molecule. In anotherexample, the determined chemical data may include ahydration/aqueousness of a molecule, which may suggest a reactiveness ofthe molecule.

Furthermore, in one embodiment, the determined chemical data may includean analysis of a chemical reaction included within the textual document,including one or more extracted details of a chemical reaction. Forexample, the determined chemical data may include an indication anddetails of precipitation/precipitates, an indication and details of anacid/base reaction, an indication and details of oxidation, anindication and details of hydration/aqueousness, an indication anddetails of solubility, etc. In another example, the determined chemicaldata may include an indication and details of a relationship between oneor more reagents, one or more reactants, and products of the chemicalreaction. In yet another example, the determined chemical data mayinclude a description of one or more type of bonds existing before thechemical reaction, formed by the chemical reaction, etc.

Further still, analyzing the textual document may include identifyingone or more chemical variables within the textual document. For example,analyzing the textual document may include identifying one or morereactions, elements, compounds, molecules, solvents, etc.

Further still, as shown in FIG. 4, method 400 may proceed with operation406, where an analysis of the determined chemical data is performed toidentify a chemical pathway. In one embodiment, the chemical pathway mayinclude an identification of a chemical reaction. For example, thechemical pathway may include an identification of a plurality of stepsinvolved in the chemical reaction. In another embodiment, the chemicalpathway may include an identification of one or more components of achemical reaction. For example, the chemical pathway may include anidentification of one or more reactants in the reaction, one or morecharacteristics of the reaction itself, one or more byproducts of thechemical reaction, etc. In yet another embodiment, the chemical pathwaymay include one of a plurality of possible outcomes of a chemicalreaction. In still another embodiment, the chemical pathway may includeone of a plurality of configurations of one or more molecules (e.g.,molecules involved in the chemical reaction, etc.).

Also, on one embodiment, performing the analysis may include identifyingone or more chemical components and/or reactions within the textualdocument and determining one or more characteristics of one or morechemical components and/or reactions identified within the textualdocument. For example, performing the analysis may include determiningfor a chemical component a number and type of atoms of the component,the aromaticity of the component, a reactivity of the component, thekinetic energy of a reaction, the activation energy of a reaction, etc.

Additionally, in one embodiment, performing the analysis of thedetermined chemical data may include assigning one or more scores toeach of the determined characteristics of the one or more chemicalcomponents and/or reactions. For example, the scores may includemetadata associated with a chemical component and/or reaction. Inanother example, each of the scores may be based on an analysis of oneor more factors associated with the chemical component and/or reaction.

For instance, reactiveness characteristics of a chemical component, suchas aromaticitiy and aqueousness, and previous successful reactionsinvolving the chemical components may be analyzed to determine areactiveness score that may be stored as metadata in association with achemical component. In another example, scores of variouscharacteristics may be used to determine a number of hydrogen atoms of acomponent, a reactivity of the component, the kinetic energy of thereaction, an activation energy of the reaction, etc.

Further, in one embodiment, the scores may be determined utilizing ananalysis of data associated with a plurality of chemical components. Forexample, predetermined rules and/or cheminformatics software may be usedto analyze the data and determine associated scores. In anotherembodiment, performing the analysis may include identifying one or morestarting components of a chemical reaction as well as one or more stepsof one or more pathways that occur during the chemical reaction.

Further still, in one embodiment, performing the analysis may includeidentifying and/or predicting one or more chemical components havingsimilar characteristics (e.g., anti-viral characteristics, etc.) to achemical component found within the textual document. In anotherembodiment, performing the analysis may include analyzing one or morechemical components within the textual document to determine one or morepatterns. In yet another embodiment, performing the analysis may includevisually reproducing one or more of the chemical components found withinthe textual document. For example, one or more molecules may be graphed(e.g., using one or more applications) and relationships betweenmolecules, edges, etc. may be determined and illustrated visually.

Also, as shown in FIG. 4, method 400 may proceed with operation 408,where a probability score is calculated for the chemical pathway. In oneembodiment, the probability score for the chemical pathway may include aprobability of one or more outcomes associated with one or moreidentified chemical components, one or more scenarios, etc.

In one embodiment, calculating the probability score may includepredicting one or more outcomes associated with one or more identifiedchemical components, one or more scenarios, etc. For example, aprobability of a reaction occurring between one or more identifiedchemical components may be determined. In another embodiment, one ormore probable results of the reaction between the one or more chemicalcomponents may be determined. In another embodiment, calculating theprobability score may include predicting a viability of one or morereactions that include one or more identified chemical components.

For example, each individual chemical component may have one or moreassociated individual scores/weights, and such weights may be combinedfor groups of chemical components and may be compared to predeterminedthresholds to determine whether the groups of chemical components willreact. In another example, one or more outcomes for one or morereactions involving the identified chemical components may bedetermined.

In addition, in one embodiment, calculating the probability score mayutilize one or more supplements. For example, one or more applicationsmay be used to predict outcomes, identify components, etc. For instance,for outcome prediction, determined chemical data may be analyzed usingknown information via an application (e.g., RDKit, etc.), which maybuild a predictive model of whether a reaction is viable. In anotherexample, the application may provide molecular properties and maytranslate the properties into a form (e.g., an annotated form, etc.)that may be used to score certain features. In yet another example, aknowledge base containing one or more known characteristics of chemicalcomponents, one or more known results of chemical reactions, etc. may beused to predict outcomes, identify components, etc.

In another embodiment, information may be added to the knowledge basebased on the results of the analysis and the calculated probabilityscore. For example, predicted outcomes, identified components, etc. maybe added to an existing knowledge base to be used for futuredetermination and analysis in association with additional textualdocuments.

In this way, results of an identification and analysis of chemicalcomponents and reactions within a textual document may build acomprehensive knowledge base of components and reactions and may utilizecalculated metadata associated with the components and reactions (e.g.,prediction, probability of success, reactivity of products, etc.) tominimize real-world experimentation required to determine viability ofchemical pathways, results of chemical reactions, determination ofsimilar components, etc.

Additionally, in one embodiment, a chemistry-based analysis of moleculesmay be performed, which may be used to build predictive models, predictchemical reactions and pathways, and to figure out how to buildmolecules that have not been previously synthesized. Additionally, anumber of synthesis steps may be reduced during a chemical synthesisprocess (e.g., from X to X-Y). Further, one or more known chemicaland/or kinetic reactions present in the textual document may beidentified and learned.

Further, in one embodiment, a molecule/compound may be identified thathas not been synthesized, and the main components of the compound may bedetermined. In another embodiment, a model may be trained based on oneor more chemical reactions and then a projection and prediction may beperformed based on the model.

FIG. 5 illustrates an exemplary chemical pathway discovery environment500, in accordance with one embodiment. As shown in FIG. 5, theenvironment 500 includes a parser and extractor 504 that retrievestextual data from a corpus 502. In one embodiment, the corpus 502includes one or more of literature, texts, web content, scanned content,etc. In another embodiment, the parser and extractor 504 parses one ormore textual elements within the corpus 502. In yet another embodiment,the parser and extractor 504 identifies and retrieves a relationshipbetween textual data within the corpus 502.

Additionally, the parser and extractor 504 is in communication with aknowledge base 506. In one embodiment, the knowledge base 506 mayinclude a listing of a plurality of chemical concepts. For example, theknowledge base 506 may include an identification and description of allknown periodic elements, all known common compounds, all known metabolicpathways, all known chemical and molecular properties, all knownchemical pathway relationships, all known chemical targets, etc. Inanother embodiment, the parser and extractor 504 may use the knowledgebase 506 to assist in the extraction of textual data from the corpus 502(e.g., help convert extracted data to a standardized format, etc.). Inyet another embodiment, the parser and extractor 504 may convert anidentified molecule in the corpus to text.

Further, the results of the parser and extractor 504 (e.g., the parsedand extracted textual data, etc.) are sent to a chemical formularesolver 508 that is also in communication with the knowledge base 506as well as chemical applications 510. In one embodiment, the chemicalformula resolver 508 may access the knowledge base 506 to verify theparsed and extracted textual data. For example, the chemical formularesolver 508 may access the knowledge base 506 to determine whether thecomponents of the parsed and extracted textual data are chemicallycorrect.

Further still, in one embodiment, the chemical formula resolver 508 mayaccess the knowledge base 506 and the chemical applications 510 todetermine a validity of the parsed and extracted textual data (e.g.,does the data make sense, have the results been seen before inliterature, etc.). In another embodiment, the chemical formula resolver508 may identify and resolve/correct errors (e.g., typographical errors,logical errors, etc.) within the parsed and extracted textual data,utilizing information stored within the knowledge base 506. In yetanother embodiment, the knowledge base 506 may be updated with one ormore analysis results, such that the knowledge base 506 may dynamicallyexpand.

Also, the results of the chemical formula resolver 508 are sent to thechemical reaction representation generator 512. In one embodiment, theresults of the chemical formula resolver 508 may include extractedtextual data that has been resolved and formatted to a standardizedformat. In another embodiment, the chemical reaction representationgenerator 512 may then create a representation of a chemical reactionbased on the received resolved and formatted data. For example, therepresentation of the chemical reaction may include an indication of oneor more reagents of the chemical reaction, one or more chemicalreactions, one or more products of the chemical reaction, etc.

In addition, in one embodiment, only a portion of a chemical reactionequation may be provided by the chemical formula resolver 508, and thechemical reaction representation generator 512 may enumerate one or morepossible reactions, one or more possible results, or one or morepossible equations from the given portion.

Furthermore, the results of the chemical reaction representationgenerator 512 (e.g., a formatted representation of a chemical reaction,etc.) are sent to a chemical reaction disambiguator 514 that is also incommunication with the knowledge base 506. In one embodiment, thechemical reaction disambiguator 514 may review, verify, and validate therepresentation of a chemical reaction, based on known chemicalreactions, known compounds, and known chemical and molecular propertiesfound in the knowledge base 506. For example, the chemical reactiondisambiguator 514 may review chemical pathways already identified fromwithin the corpus 502 stored in the knowledge base 506 and may comparethose pathways to one or more molecules that are associated with thechemical reaction to confirm the validity of the chemical reaction.

Further still, the results of the chemical reaction disambiguator 514(e.g., a verified and formatted representation of a chemical reaction,etc.) are sent to a chemical pathway scorer 516 that applies a postprocess scoring methodology 518 to the representation of the chemicalreaction. In one embodiment, the post process scoring methodology 518may include a plurality of criteria that influence a score determinedfor a plurality of elements within the representation of the chemicalreaction. For example, the criteria within the post process scoringmethodology 518 may include one or more of a chemical similarity checkand associated scoring, a stoichiometry check, an aromatic scoring, abonds and solubility scoring, a reaction type tendency scoring, etc. Inanother example, each of the criteria may be compared against therepresentation of the chemical reaction to determine an individual scoreassociated with that specific pathway, which may be stored or combinedwith other scores associated with other criteria.

Also, the post process scoring methodology 518 is linked to the chemicalapplications 510. In one embodiment, the chemical applications 510 mayinclude one or more applications that assist with verifying one or morechemical elements, determining certain elements like aromaticity, bonds,reaction types, etc. In this way, the chemical applications may help thechemical pathway scorer 516 implement the scoring methodology 518. Inanother embodiment, the chemical applications may include one or more ofTversky, Fraggle, RDKit, etc.

Additionally, the results of the chemical pathway scorer 516 (e.g., ascored, verified, and formatted representation of a chemical reaction,etc.) is sent to the pathway probability calculator 520. In oneembodiment, the pathway probability calculator 520 may determine aprobability of a successful chemical reaction, given the scores computedby the chemical pathway scorer 516. In another embodiment, the pathwayprobability calculator 520 may determine a probability that there willbe a viable chemical pathway corresponding to the receivedrepresentation.

Further, the pathway probability calculator 520 is linked to theknowledge base 506. In one embodiment, the pathway probabilitycalculator 520 may identify one or more known chemical targets withinthe knowledge base 506 and may compare the known chemical targets to thereceived representation of the chemical reaction to determine whetherthe pathway indicated by the received representation is a viable pathwayto try to achieve (e.g., via experimentation, etc.).

In one embodiment, the determination of a viable pathway may utilize thestoichiometry of the chemical reaction, including the solubility, thereaction tendency of the reactants, and the similarity score to a targetmolecule proportional to the aromatic score and bond type score of thereactants. For example, S₁ may represent a solubility score, t₁ mayrepresent a reaction tendency score, c₁ may represent a corpus tendencyscore, l₁ may represent a similarity score, r₁ may represent asimilarity reference score, al may represent an aromaticity score, andb₁ may represent a bond type score.

In another example, the solubility score may include a normalized valueof the solubility of the molecule at a specific temperature andatmospheric pressure in 100 ML of the solvent. The value may include anamount of the compound required. For example, BaCl₂ may have asolubility score at 0.358 based on its solubility of 35.8 g/100 mL at 20degrees Celsius in water. In another embodiment, the reaction tendencyscore may include the chemical affinity score if one can be found from alookup table; otherwise it may be a number of bond acceptors or donorsthe molecule contains (e.g., hydrogen-bond donors (h-bond donors),etc.).

Additionally, in one embodiment, a corpus tendency may include a numberof passages found with the same type of chemical reaction normalized bythe total number of passages in the documents parsed. In anotherembodiment, a similarity score may include the Tversky score for themolecule, and the similarity reference score may include a number ofpassages with the same or similar compounds in the corpus normalized tothe total number of passages in the corpus.

Further, in one embodiment, a bond type scores may include point scores,for example, 25 points for single bonds, 40 points for double bonds and60 points for triple bond compounds. The aromatic score may include 1point if not applicable; however, if applicable, it may include 10points for each aromatic feature shape, ring, bonds, planar anddelocalized electrons. A representative probability score computationequation may include a sum of the scores for each molecule that is areagent in the equation, or using LaTeX Mathematical equationsProbabilityScore=\sum_{i=1}̂{n}\frac{S_i+(t_i*c_i)+(l_i*r_i))}{(a_i+b_i)}.

Table 1 illustrates an exemplary equation that calculates theprobability score as a sum of the scores for each molecule that is areagent in the equation. Of course, it should be noted that theexemplary equation shown in Table 1 is set forth for illustrativepurposes only, and thus should not be construed as limiting in anymanner.

TABLE 1${{Probability}\mspace{14mu} {Score}} = {\sum\limits_{i = 1}^{n}\; \frac{ {S_{i} + ( {t_{i}*c_{i}} ) + ( {l_{i}*r_{i}} )} )}{( {a_{i} + b_{i}} )}}$

Now referring to FIG. 6, a flowchart of a method 600 for performingreaction corpus scoring is shown according to one embodiment. The method600 may be performed in accordance with the present invention in any ofthe environments depicted in FIGS. 1-5, among others, in variousembodiments. Of course, more or less operations than those specificallydescribed in FIG. 6 may be included in method 600, as would beunderstood by one of skill in the art upon reading the presentdescriptions.

Each of the steps of the method 600 may be performed by any suitablecomponent of the operating environment. For example, in variousembodiments, the method 600 may be partially or entirely performed byone or more servers, computers, or some other device having one or moreprocessors therein. The processor, e.g., processing circuit(s), chip(s),and/or module(s) implemented in hardware and/or software, and preferablyhaving at least one hardware component may be utilized in any device toperform one or more steps of the method 600. Illustrative processorsinclude, but are not limited to, a central processing unit (CPU), anapplication specific integrated circuit (ASIC), a field programmablegate array (FPGA), etc., combinations thereof, or any other suitablecomputing device known in the art.

As shown in FIG. 6, method 600 may initiate with operation 602, wherethe reaction corpus scoring retrieves a compound with similar reactiontypes from one or more passages in the corpora being used. In oneembodiment, the reaction types may include melting, sublimation,evaporation, and condensation, oxidation, precipitation, etc.Additionally, method 600 may proceed with operation 604, where similarcompounds with a high Tversky similarity score to the compound reactantare searched, found, and counted.

Further, method 600 may proceed with operation 606, where a total numberof passages that matched in similarity or reaction type during thesearch for similar compounds is noted. In one embodiment, one or more ofoperations 602-606 may utilize reaction and compound passage data storedin a shared database.

Further still, method 600 may proceed with operation 608, where thecorpus tendency score is calculated by multiplying an affinity or theh-bond donors or acceptors in the compound by the number of matchedpassages divided by the total number of passages. In another embodiment,the similarity reference score may include matched similar compoundpassages that are over a Tversky threshold value and that are divided bythe total number of passages. In one embodiment, one or more ofoperations 606-608 may utilize the retrieved Tversky threshold stored ina shared database. Also, method 600 may proceed with operation 610,where the corpus tendency and similarity scores are stored in a corpusreaction database for use.

In this way, a pathway probability calculator may determine whether anexperiment itself is viable and whether the experiment is it going toreact the way it is intended, based on an analysis of corpus textualdata. Also, one or more outcomes of the experiment may be predicted,based on the analysis.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein includes anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which includes one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

Moreover, a system according to various embodiments may include aprocessor and logic integrated with and/or executable by the processor,the logic being configured to perform one or more of the process stepsrecited herein. By integrated with, what is meant is that the processorhas logic embedded therewith as hardware logic, such as an applicationspecific integrated circuit (ASIC), a FPGA, etc. By executable by theprocessor, what is meant is that the logic is hardware logic; softwarelogic such as firmware, part of an operating system, part of anapplication program; etc., or some combination of hardware and softwarelogic that is accessible by the processor and configured to cause theprocessor to perform some functionality upon execution by the processor.Software logic may be stored on local and/or remote memory of any memorytype, as known in the art. Any processor known in the art may be used,such as a software processor module and/or a hardware processor such asan ASIC, a FPGA, a central processing unit (CPU), an integrated circuit(IC), a graphics processing unit (GPU), etc.

It will be clear that the various features of the foregoing systemsand/or methodologies may be combined in any way, creating a plurality ofcombinations from the descriptions presented above.

It will be further appreciated that embodiments of the present inventionmay be provided in the form of a service deployed on behalf of acustomer to offer service on demand.

While various embodiments have been described above, it should beunderstood that they have been presented by way of example only, and notlimitation. Thus, the breadth and scope of a preferred embodiment shouldnot be limited by any of the above-described exemplary embodiments, butshould be defined only in accordance with the following claims and theirequivalents.

What is claimed is:
 1. A computer-implemented method, comprising:identifying a textual document; determining chemical data within thetextual document; performing an analysis of the chemical data toidentify a chemical pathway; and calculating a probability score for thechemical pathway.
 2. The computer-implemented method of claim 1, whereinthe textual document includes a research paper, a textbook, a blog post,and a web page.
 3. The computer-implemented method of claim 1, whereindetermining the chemical data within the textual document includesparsing the textual document and analyzing a plurality of components ofthe textual document.
 4. The computer-implemented method of claim 1,wherein determining the chemical data within the textual documentincludes identifying and analyzing relationships between a plurality ofterms within the textual document.
 5. The computer-implemented method ofclaim 1, wherein the chemical data includes data identifying one or moreof chemicals, compounds, and molecules.
 6. The computer-implementedmethod of claim 1, wherein the chemical data includes one or moredetails of one or more chemical reactions.
 7. The computer-implementedmethod of claim 1, wherein calculating the probability score includesdetermining and weighting one or more characteristics of one or morechemical components found within the textual document.
 8. Thecomputer-implemented method of claim 1, wherein calculating theprobability score includes identifying one or more patterns within oneor more chemical components found within the textual document.
 9. Thecomputer-implemented method of claim 1, wherein calculating theprobability score includes predicting an outcome of a chemical reaction,utilizing the chemical data.
 10. The computer-implemented method ofclaim 1, wherein calculating the probability score includes comparingthe chemical data to a knowledge base to determine one or morecharacteristics of the chemical data.